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Complementary Variable- and Person-Centered Approaches to the Dimensionality of Psychometric Constructs: Application to Psychological Wellbeing at Work

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Abstract

Purpose

This study illustrates complementary variable- and person-centered approaches allowing for a more complete investigation of the dimensionality of psychometric constructs. Psychometric measures often assess conceptually related facets of global overarching constructs based on the implicit or explicit assumption that these overarching constructs exist as global entities including conceptually related specificities mapped by the facets. Proper variable- and person-centered methodologies are required to adequately reflect the dimensionality of these constructs.

Design/Methodology/Approach

We illustrate these approaches using employees’ (N = 1077) ratings of their psychological wellbeing at work.

Findings

The results supported the added value of the variable-centered approach proposed here, showing that employees’ ratings of their own wellbeing simultaneously reflect a global overarching wellbeing construct, together with a variety of specific wellbeing dimensions. Similarly, the results show that anchoring person-centered analyses into these variable-centered results helps to achieve a more precise depiction of employees’ wellbeing profiles.

Implications

The variable-centered bifactor exploratory structural equation modeling (ESEM) framework provides a way to fully explore these sources of psychometric multidimensionality. Similarly, whenever constructs are characterized by the co-existence of overarching constructs with specific dimensions, it becomes important to properly disaggregate these two components in person-centered analyses. In this context, person-centered analyses need to be clearly anchored in the results of preliminary variable-centered analyses.

Originality/Value

Substantively, this study proposes an improved representation of employees’ wellbeing at work. Methodologically, this study aims to pedagogically illustrate the application of recent methodological innovations to organizational researchers.

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Notes

  1. This partitioning is made possible by the orthogonality of the factors, which forces the covariance shared among all items to be fully absorbed into the G-factor, while the S-factors represent the covariance shared among a subset of items but not with the others. Similar models in which the specific factors are allowed to correlate thus allow some of the variance shared among multiple sets of items to be modeled separately from the global factor, importantly changing the meaning of the model. Such non-orthogonal models are typically used to incorporate methodological controls in a model rather than to estimate meaningful G- and S-Factors. In one such example, the global factor has been proposed to control for responses tendencies shared across all items (Podsakoff et al. 2003), albeit with limited success based on the demonstration that meaningful information was still absorbed into this global “method” factor (Richardson et al. 2009). More typically, this approach is used to represent a global trait factor assessed by multiple sources of information (i.e., multi-trait-multi-method) represented by the specific factors (Eid 2000).

  2. The person-centered approach presented in the present study focuses on latent profile analyses rather than more common cluster analyses. Readers interested in a comparison of both methods are referred to Meyer and Morin (2016), Morin et al. (2011), and Vermunt and Magidson (2002).

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Acknowledgments

The research was supported by a GRF fund from the Research Grants Council of Hong Kong SAR (Ref. No.: 843911) awarded to the first, third, and fourth authors. Preparation of this article was also supported by a research grant from the Australian Research Council (LP140100100) awarded to the first and third authors.

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    Authors and Affiliations

    1. Institute for Positive Psychology and Education, Australian Catholic University, Strathfield Campus, Locked Bag 2002, Strathfield, NSW, 2135, Australia

      Alexandre J. S. Morin & Herbert W. Marsh

    2. Département de Psychologie, Université de Montréal, Montreal, QC, Canada

      Jean-Sébastien Boudrias & Véronique Dagenais-Desmarais

    3. Faculty of Education, King Saud University, Riyadh, Saudi Arabia

      Herbert W. Marsh

    4. The Education University of Hong Kong, Tai Po, Hong Kong

      Dennis M. McInerney

    5. Department of Psychology, Macquarie University, Sydney, Australia

      Isabelle Madore

    6. Département des fondements et pratiques en éducation, Faculté des sciences de l’éducation, Université Laval, Quebec, QC, Canada

      David Litalien

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    1. Alexandre J. S. Morin
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    2. Jean-Sébastien Boudrias
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    Correspondence to Alexandre J. S. Morin.

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    Alexandre J. S. Morin and Jean-Sébastien Boudrias have contributed equally to this article and their order was determined at random: both should be considered first authors.

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    Morin, A.J.S., Boudrias, JS., Marsh, H.W. et al. Complementary Variable- and Person-Centered Approaches to the Dimensionality of Psychometric Constructs: Application to Psychological Wellbeing at Work. J Bus Psychol 32, 395–419 (2017). https://doi.org/10.1007/s10869-016-9448-7

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